MATLAB与机器学习入门培訓

為期3天的課程，帶您瀏覽MATLAB主屏幕和窗口，包括......

• 如何使用matlab作為caluclator並繪製基本曲線
• 如何創建自己的自定義函數和腳本

這個為期四天的課程使用Matlab提供圖像處理基礎。您將練習如何更改和增強圖像，甚至從圖像中提取圖案。您還將學習如何構建2D濾鏡並將其應用於圖像。

示例和練習演示了在整個分析過程中使用適當的Matlab和圖像處理工具箱功能。

This three-day course provides a comprehensive introduction to the MATLAB technical computing environment. The course is intended for beginning users and those looking for a review. No prior programming experience or knowledge of MATLAB is assumed. Themes of data analysis, visualization, modeling, and programming are explored throughout the course. Topics include:

•     Working with the MATLAB user interface
•     Entering commands and creating variables
•     Analyzing vectors and matrices
•     Visualizing vector and matrix data
•     Working with data files
•     Working with data types
•     Automating commands with scripts
•     Writing programs with logic and flow control
•     Writing functions

In this instructor-led, live training, participants will learn how to use Matlab to design, build, and visualize a convolutional neural network for image recognition.

By the end of this training, participants will be able to:

• Build a deep learning model
• Automate data labeling
• Work with models from Caffe and TensorFlow-Keras
• Train data using multiple GPUs, the cloud, or clusters

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

In the first part of this training, we cover the fundamentals of MATLAB and its function as both a language and a platform.  Included in this discussion is an introduction to MATLAB syntax, arrays and matrices, data visualization, script development, and object-oriented principles.

In the second part, we demonstrate how to use MATLAB for data mining, machine learning and predictive analytics. To provide participants with a clear and practical perspective of MATLAB's approach and power, we draw comparisons between using MATLAB and using other tools such as spreadsheets, C, C++, and Visual Basic.

In the third part of the training, participants learn how to streamline their work by automating their data processing and report generation.

Throughout the course, participants will put into practice the ideas learned through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough grasp of MATLAB's capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation.

Assessments will be conducted throughout the course to gauge progress.

Format of the Course

• Course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation.

Note

• Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange.

這種以講師為主導的香港現場現場培訓面向希望學習如何使用Matlab對動態問題進行數值類比的初學者或工程師。

在培訓結束時，參與者將能夠：

• 瞭解動態分析的基礎知識。
• 使用 Matlab 執行解析解和數值解。
• 使用不同的方法推導運動方程。

MATLAB integrates computation, visualization and programming in an easy to use environment. It offers Financial Toolbox, which includes the features needed to perform mathematical and statistical analysis of financial data, then display the results with presentation-quality graphics.

This instructor-led training provides an introduction to MATLAB for finance. We dive into data analysis, visualization, modeling and programming by way of hands-on exercises and plentiful in-lab practice.

By the end of this training, participants will have a thorough understanding of the powerful features included in MATLAB's Financial Toolbox and will have gained the necessary practice to apply them immediately for solving real-world problems.

Audience

• Financial professionals with previous experience with MATLAB

Format of the course

• Part lecture, part discussion, heavy hands-on practice

This course provides a comprehensive introduction to the MATLAB technical computing environment + an introduction to using MATLAB for financial applications. The course is intended for beginning users and those looking for a review. No prior programming experience or knowledge of MATLAB is assumed. Themes of data analysis, visualization, modeling, and programming are explored throughout the course. Topics include:

• Working with the MATLAB user interface
• Entering commands and creating variables
• Analyzing vectors and matrices
• Visualizing vector and matrix data
• Working with data files
• Working with data types
• Automating commands with scripts
• Writing programs with logic and flow control
• Writing functions
• Using the Financial Toolbox for quantitative analysis

Predictive analytics is the process of using data analytics to make predictions about the future. This process uses data along with data mining, statistics, and machine learning techniques to create a predictive model for forecasting future events.

In this instructor-led, live training, participants will learn how to use Matlab to build predictive models and apply them to large sample data sets to predict future events based on the data.

By the end of this training, participants will be able to:

• Create predictive models to analyze patterns in historical and transactional data
• Use predictive modeling to identify risks and opportunities
• Build mathematical models that capture important trends
• Use data from devices and business systems to reduce waste, save time, or cut costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Prescriptive analytics is a branch of business analytics, together with descriptive and predictive analytics. It uses predictive models to suggest actions to take for optimal outcomes, relying on optimization and rules-based techniques as a basis for decision making.

In this instructor-led, live training, participants will learn how to use Matlab to carry out prescriptive analytics on a set of sample data.

By the end of this training, participants will be able to:

• Understand the key concepts and frameworks used in prescriptive analytics
• Use MATLAB and its toolboxes to acquire, clean and explore data
• Use rules-based techniques including inference engines, scorecards, and decision trees to make decisions based on different business scenarios
• Use Monte Carlo simulation to analyze uncertainties and ensure sound decision making
• Deploy predictive and prescriptive models to enterprise systems

Audience

• Business analysts
• Operations planners
• Functional managers
• BI (Business Intelligence) team members

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

這個為期兩天的課程全面介紹了MATLAB技術計算環境。本課程面向初學者和尋求評審的用戶。沒有先前的編程經驗或MATLAB知識。在整個課程中探索了數據分析，可視化，建模和編程的主題。

這種以講師為主導的香港現場培訓（現場或遠端）針對的是希望探索和/或過渡到Python進行數據分析和可視化的Matlab使用者。

在培訓結束時，參與者將能夠：

• 安裝和配置 Python 開發環境。
• 瞭解 Matlab 和 Python 語法之間的異同。
• 使用 Python 從各種資料集中取得見解。 
• 將現有 Matlab 應用程式轉換為 Python。 
• 集成 Matlab 和 Python 應用程式。

Simulink是一個用於建模，模擬和分析多域動態系統的圖形化編程環境。

本課程包含有關MATLAB作為通信的強大仿真工具的綜合材料。本課程的目的是將MATLAB不僅作為通用編程語言引入，而且強調了作為仿真工具的極其強大的MATLAB功能的作用。用於說明課程材料的示例不僅僅是直接使用MATLAB命令，而是經常代表真正的問題。